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Role of batch size in scheduling optimization of flexible manufacturing system using genetic algorithm

机译:批次大小在遗传算法中柔性制造系统调度优化的作用

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摘要

Abstract Flexible manufacturing system (FMS) readily addresses the dynamic needs of the customers in terms of variety and quality. At present, there is a need to produce a wide range of quality products in limited time span. On-time delivery of customers’ orders is critical in make-to-order (MTO) manufacturing systems. The completion time of the orders depends on several factors including arrival rate, variability, and batch size, to name a few. Among those, batch size is a significant construct for effective scheduling of an FMS, as it directly affects completion time. On the other hand, constant batch size makes MTO less responsive to customers’ demands. In this paper, an FMS scheduling problem with n jobs and m machines is studied to minimize lateness in meeting due dates, with focus on the impact of batch size. The effect of batch size on completion time of the orders is investigated under following strategies: (1) constant batch size, (2) minimum part set, and (3) optimal batch size. A mathematical model is developed to optimize batch size considering completion time, lateness penalties and setup times. Scheduling of an FMS is not only a combinatorial optimization problem but also NP-hard problem. Suitable solutions of such problems through exact methods are difficult. Hence, a meta-heuristic Genetic algorithm is used to optimize scheduling of the FMS.
机译:摘要灵活的制造系统(FMS)在各种和质量方面易于解决客户的动态需求。目前,需要在有限的时间范围内生产各种优质产品。随时交付客户的订单在按订单(MTO)制造系统中至关重要。订单的完成时间取决于包括到达率,可变性和批量大小的几个因素,以命名几个。其中,批量大小是用于有效调度FMS的重要构建体,因为它直接影响完成时间。另一方面,恒定的批量大小使MTO对客户的需求不太响应。在本文中,研究了N个作业和M机器的FMS调度问题,以最大限度地减少满足应有日期的迟到,专注于批量尺寸的影响。在以下策略下,研究了批量大小对订单完成时间的影响:(1)恒定批量大小,(2)最小零件集,(3)最佳批量尺寸。开发了一种数学模型以考虑完成时间,迟到的惩罚和设置时间来优化批量大小。 FMS的调度不仅是组合优化问题,而且是NP难题。通过精确方法难以解决这些问题的合适解决方案。因此,使用元 - 启发式遗传算法来优化FMS的调度。

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